Sleep state estimation device and program product for providing a computer with a sleep state estimation function

• US 20050080349A1
• Filed: 10/12/2004
• Published: 04/14/2005
• Est. Priority Date: 10/14/2003
• Status: Active Grant

• Current Assignee: Sanyo Electric Company Limited (Panasonic Holdings Corporation)
• Original Assignee: Sanyo Electric Company Limited (Panasonic Holdings Corporation)
• Inventors: Yamamoto, Yasushi, Yoneda, Fumiiki, Fujiwara, Yoshihisa, Okada, Shima
• Granted Patent: US 7,150,718 B2
• Time in Patent Office: Days
• US Class Current: 600/534
• CPC Class Codes: A61B 2562/0261 Strain gauges
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/1135 by monitoring thoracic expansion
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses

Abstract

An object of the present invention is to provide a sleep state estimation device capable of estimating a sleep state (deep sleep, light sleep) in real time with relative simplicity. Voltage variations resulting from human respiratory movement are measured for each given period to calculate from the measurement results positive voltage peak values and time intervals between adjacent peaks. The obtained peak values and peak intervals are used to calculate a mean peak interval value A, a coefficient of variation B based on dispersion of the peak intervals, and a coefficient of variation C based on the peak values. The sleep state in this period is estimated from the calculation results. More specifically, referring to FIG. 5, the sleep state is estimated as a “wakeful state” or a “hypnagogic state” by checking whether the mean value A is larger or smaller than a threshold a and whether the coefficient of variation C is larger or smaller than a threshold c (S105) whereas the sleep state is estimated as the “hypnagogic state”, “light sleep” or “deep sleep” by checking whether the coefficient of variation B is larger or smaller than a threshold b and whether the coefficient of variation C is larger or smaller than the threshold c (S109, S113, S116, S117).

Claims

1. A sleep state estimation device for estimating a sleep state, comprising:

vital signs information processing means for extracting respiratory signals from output signals of a vital signs information sensor; and

sleep state estimating means for estimating the sleep state based on the respiratory signals outputted by the vital signs information processing means.

2. A sleep state estimation device according to claim 1,

wherein the sleep state estimating means includes:

peak calculating means for calculating respiratory signal peak values in a given period from the respiratory signals outputted by the vital signs information processing means; and

peak interval calculating means for calculating respiratory signal peak intervals in the given period from the respiratory signals, and

wherein the sleep state estimating means estimates the sleep state based on the peak values and from the peak intervals.

3. A sleep state estimation device according to claim 2,

wherein the sleep state estimating means further includes:

first coefficient of variation calculating means for calculating, from the peak intervals obtained by the peak interval calculating means, a first coefficient of variation which is based on dispersion of the peak intervals; and

second coefficient of variation calculating means for calculating, from the peak values obtained by the peak calculating means, a second coefficient of variation which is based on dispersion of the peak values, and

wherein the sleep state estimating means estimates the sleep state by comparing the first coefficient of variation and the second coefficient of variation against given thresholds.

4. A sleep state estimation device according to claim 2,

wherein the sleep state estimating means further includes:

mean peak interval calculating means for calculating, from the peak intervals obtained by the peak interval calculating means, a mean value of the peak intervals; and

second coefficient of variation calculating means for calculating, from the peak values obtained by the peak calculating means, a second coefficient of variation which is based on dispersion of the peak values, and

wherein the sleep state estimating means estimates the sleep state by comparing the mean peak interval value and the second coefficient of variation against given thresholds.

5. A sleep state estimation device according to claim 2,

wherein the sleep state estimating means further includes:

first coefficient of variation calculating means for calculating, from the peak intervals obtained by the peak interval calculating means, a first coefficient of variation which is based on dispersion of the peak intervals;

second coefficient of variation calculating means for calculating, from the peak values obtained by the peak calculating means, a second coefficient of variation which is based on dispersion of the peak values; and

mean peak interval calculating means for calculating, from the peak intervals obtained by the peak interval calculating means, the mean value of the peak intervals, and

wherein the sleep state estimating means estimates the sleep state by comparing the first coefficient of variation and the second coefficient of variation against given thresholds, and by comparing the mean peak interval value and the second coefficient of variation against given thresholds.

6. A sleep state estimation device according to any one of claims 1 through 5, further comprising:

wakeful state detecting means for detecting a wakeful state; and

estimation aborting means for stopping, upon detection of the wakeful state by the wakeful state detecting means, sleep state estimation the sleep state estimating means is conducting.

7. Asleep state estimation device according to claim 6, wherein the wakeful state detecting means detects the wakeful state by extracting body movement signals from output signals of the vital signs information sensor.

8. A computer product for providing a computer with a sleep state estimation function, comprising:

a vital signs information processing step of extracting respiratory signals from output signals of a vital signs information sensor; and

a sleep state estimating step of estimating a sleep state based on the respiratory signals extracted in the vital signs information processing step.

9. A computer product according to claim 8,

wherein the sleep state estimating step includes:

a peak calculating step of calculating respiratory signal peak values in a given period from the respiratory signals extracted in the vital signs information processing step; and

a peak interval calculating step of calculating respiratory signal peak intervals in the given period from the respiratory signals, and

wherein the sleep state is estimated based on the peak values and the peak intervals in the sleep state estimating step.

10. A compute product according to claim 9,

wherein the sleep state estimating step further includes:

a first coefficient of variation calculating step of calculating, from the peak intervals obtained in the peak interval calculating step, a first coefficient of variation which is based on dispersion of the peak intervals; and

a second coefficient of variation calculating step of calculating, from the peak values obtained in the peak calculating step, a second coefficient of variation which is based on dispersion of the peak values, and

wherein the sleep state is estimated by comparing the first coefficient of variation and the second coefficient of variation against given thresholds in the sleep state estimating step.

11. A computer product according to claim 9,

wherein the sleep state estimating step further includes:

a mean peak interval calculating step of calculating, from the peak intervals obtained in the peak interval calculating step, a mean value of the peak intervals; and

a second coefficient of variation calculating step of calculating, from the peak values obtained in the peak calculating step, a second coefficient of variation which is based on dispersion of the peak values, and

wherein the sleep state is estimated by comparing the mean peak interval value and the second coefficient of variation against given thresholds in the sleep state estimating step.

12. A computer product according to claim 9,

wherein the sleep state estimating step further includes:

a first coefficient of variation calculating step of calculating, from the peak intervals obtained in the peak interval calculating step, a first coefficient of variation which is based on dispersion of the peak intervals;

a second coefficient of variation calculating step of calculating, from the peak values obtained in the peak calculating step, a second coefficient of variation which is based on dispersion of the peak values; and

a mean peak interval calculating step of calculating, from the peak intervals obtained in the peak interval calculating step, the mean value of the peak intervals, and

wherein the sleep state is estimated by comparing the first coefficient of variation and the second coefficient of variation against given thresholds and by comparing the mean peak interval value and the second coefficient of variation against given thresholds in the sleep state estimating step.

13. A computer product device according to any one of claims 8 through 12, further comprising:

a wakeful state detecting step of detecting a wakeful state; and

an estimation aborting step of stopping, upon detection of the wakeful state in the wakeful state detecting step, sleep state estimation conducted in the sleep state estimation step.

14. A computer product according to claim 13, wherein the wakeful state is detected by extracting body movement signals from output signals of the vital signs information sensor in the wakeful state detecting step.